Computer Vision for Traffic Monitoring

Abstract

This project examined computer vision applications for traffic monitoring and safety analysis. The focus was on evaluating the open-source computer vision code that we developed. Three case studies were completed using our computer vision code. The code was written in Python and uses a detection model called YOLOv8. The first case study demonstrated how user counts can be obtained from video feeds and provided examples of insights that can be drawn from these counts. The second case study used computer vision to create visualizations of user movements at intersections. The third case study developed and demonstrated the application of a new surrogate safety measure for pedestrian and bicyclist safety. Shortcomings and future opportunities of open-source computer vision systems are discussed.